The transmission and control of XDR TB in South Africa: an operations research and mathematical modelling approach

Abstract

Extensively drug-resistant tuberculosis (XDR TB) has emerged as a threat to TB control efforts in several high-burden areas, generating international concern. XDR TB is now found in every region of the world, but appears most worrisome in the context of HIV and in resource-limited settings with congregate hospital wards. Here, we examine the emergence and transmission dynamics of the disease, incorporating the mathematical modelling literature related to airborne infection and epidemiological studies related to the operations of TB control programmes in resource-limited settings. We find that while XDR TB may present many challenges in the setting of resource constraints, the central problems highlighted by the emergence of XDR TB are those that have plagued TB programmes for years. These include a slow rate of case detection that permits prolonged infectiousness, the threat of airborne infection in enclosed spaces, the problem of inadequate treatment delivery and treatment completion, and the need to develop health systems that can address the combination of TB and poverty. Mathematical models of TB transmission shed light on the idea that community-based therapy and rapid detection systems may be beneficial in resource-limited settings, while congregate hospital wards are sites for major structural reform.

Fig. 1

Results of the Wells–Riley model, showing the proportion of susceptibles infected by a single infectious TB case over different durations of exposure. Note that in the context of XDR TB epidemic in South Africa, average hospital admission times in congregate wards were ~22 days [24]. Three simulations are shown, using common parameter values (κ=0·48 m³/h [75]; VA=402 m³/h, an average among mechanically ventilated rooms [78]), where the number of infectious quanta is varied from the Riley's estimate among HIV-negative TB in-patients (q=1·3, [70]) to Escombe's estimate among HIV-positive TB in-patients (q=8·2 [69]) to Nardell's estimate for an untreated TB patient (q=13 [71]).

Fig. 2

Results of a simple simulation model of XDR TB, incorporating both community and nosocomial transmission (see Appendix). In this simulation, an initially nosocomial outbreak can lead to eventual community-based transmission, even though this model assumes the transmission fitness of the XDR TB strain is only 35% that of drug-susceptible strains (an average among MDR TB strains [8]). The parameters in the simulation are: κ=0·48 m³/h [75]; VA=402 m³/h (78); q=1·3 [70]; 20% HIV prevalence [27], and 40 in-patient beds [65], and the resulting cumulative incidence curve is of similar rate and magnitude to the observed XDR TB epidemic in KwaZulu-Natal [89].

Fig. 3

The risk of nosocomial super-infection by XDR TB can outweigh the benefit of reduced community-based transmission when sufficient numbers of people are quarantined together on multi-person (congregate) TB wards. Most South African health facilities lack individual isolation units, hence quarantine is enforced in congregate settings. The degree to which such perversity will occur will depend on the congregate ward conditions and community contact rates, which are generally difficult to estimate. In this simulation using baseline parameters from KwaZulu-Natal, South Africa (see Appendix; which uses the same parameters as Fig. 2), not allowing suspects to be discharged from congregate in-patient wards and increasing ward capacity (employing the parameters described in a recent South African government strategy document [51]) increased the incidence of XDR TB. Providing community-based therapy (with the parameters specified in Mitnick et al. [64]) reduced the incidence of XDR TB, as slight increases to community-based risk were outweighed by large decreases in nosocomial risk.

Fig. A1

Flow diagram for the simple model of TB transmission.